The introduction of the CUCKOO Workgroup
(PTMs), also called as
covalent modifications, are chemical modifying
processes of proteins after their translation.
By proteolytic cleavage of peptide chains,
by adding various functional groups (e.g.
phosphorylation) to individual amino acids,
or by altering the chemical properties of
amino acid residues (e.g. citrullination),
various PTMs create or disrupt covalent bonds
to change structures, localizations and functions
of proteins significantly, play essential
roles in almost all of cellular
signaling pathways & networks,
and determine the cellular dynamics and plasticity.
Although more than 350 types of PTMs have
been discovered, only a few of them have been
well-characterized due to the lack of sufficient
data for analyses. Experimental identification
of PTM substrates with their sites is labor-intensive
and often limited by the availability and
optimization of enzymatic reaction. In
silico prediction could be a promising
strategy to conduct preliminary analyses and
greatly reduce the number of potential targets
that need further in vivo or in
Previously, several types of PTMs have been investigated using computational approaches, e.g. phosphorylation, glycosylation, sulfation and myristoylation, etc. However, the prediction performances of these programs still remain to be improved. The Cuckoo Workgroup focused on developing more rigorous computational models and designing more efficient algorithms to enhance the research of PTMs. Besides the well-know PTM of phosphorylation, we also considered several other new PTMs, including sumoylation, palmitoylation and Lysine/Arginine methylation, etc. We developed several easy-to-use online web tools and downloadable softwares. For example, we constructed GPS and PPSP for prediction of phosphorylation sites, based on GPS and Bayesian Decision Theory algorithms, respectively. And we designed the CSS-Palm to predict the palmitoylation sites. Also, we developed the online tool of MeMo to predict Lysine/Arginine methylation sites, with SVMs algorithm. Moreover, we constructed an online tool of SUMOsp to predict sumoylation sites, mainly with the GPS algorithm. We also surveyed the the functional diversity of SUMO substrates, and carried out large-scale prediction of Protein Kinase A (PKA) specific substrates. More analyses will be available in the near future.
Our aim is to develop novel algorithms and computational softwares for understanding the temporally and spatially regulatory roles of post-translational modifications involved in cellular signaling pathways and networks. We believe our and others computational studies together with experimental identifications will propel the research of PTMs into a new phase.